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Temporal Dynamics and Security Assessment of SRT Protocol: A 96-Day Longitudinal Analysis of Production Streaming Infrastructure

Ahmed Fouad Kadhim Koysha · 2026 · Journal of Communications

DOI: 10.12720/jcm.21.4.544-564 · cited by 0 works (OpenAlex) · open-access PDF

Spanish

Este estudio guía un análisis longitudinal de 96 días del comportamiento del protocolo de Transporte Fiable Seguro (SRT) en un entorno de transmisión de producción entre Irak y Turquía, examinando 262,672 muestras de datos de transporte y 5,033,104 mediciones de recursos del sistema recopiladas entre octubre de 2025 y enero de 2026. La investigación aborda los patrones temporales, las relaciones de recursos del sistema, la vulnerabilidad al ataque y la detección de anomalías. Los resultados revelan una variación temporal significativa: el reconocimiento negativo muestra una variación horaria de 7,6 veces y una variación diaria de 11,05 veces (p < 0,001), aunque con pequeñas dimensiones de efecto (eta^2 < 0,04), lo que indica que el período temporal explica menos del 4 por ciento de la variación total del estudio de seguridad. La utilización de la

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Abstract

This study presents a 96-day longitudinal analysis of Secure Reliable Transport (SRT) protocol behavior in a production streaming environment between Iraq and Turkey, examining 262,672 transport metric samples and 5,033,104 system resource measurements collected between October 2025 and January 2026. The research addresses temporal patterns, system-resource relationships, attack vulnerability, and anomaly detection. Results reveal significant temporal variation: Negative Acknowledgment exhibits 7.6-fold hourly variation and 11.5-fold daily variation (p < 0.001), though with small effect sizes (eta^2 < 0.04), indicating that temporal period explains less than 4 percent of total variance. Central Processing Unit (CPU) utilization emerges as the strongest system-level correlate of transport variation (r = 0.617 with NAK rate). Controlled User Datagram Protocol (UDP) flood experiments at 500 packets per second cause CPU increases of 176 to 806 percent, while SRT transport metrics change by only plus or minus 13 percent demonstrating protocol resilience through the Automatic Repeat Request mechanism. An unexpected anomaly reaching 97.7 percent CPU enabled signature-based differentiation between attack types. A Z-score anomaly detection method outperforms fixed thresholds, detecting all 7 security events. This study contributes the longest temporal characterization of SRT metrics reported to date, the first system-SRT correlation analysis, and the first controlled security assessment of SRT infrastructure. These findings provide actionable guidance for capacity planning, security hardening, and multi-metric monitoring of production SRT deployments.

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Topics: Computer science, Dynamics (music), Production (economics), Real-time computing, System dynamics, Computer network

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